Automatic Speech Recognition
Transformers.js
PyTorch
ONNX
Vietnamese
whisper
audio
hf-asr-leaderboard
Instructions to use huuquyet/PhoWhisper-medium with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers.js
How to use huuquyet/PhoWhisper-medium with Transformers.js:
// npm i @huggingface/transformers import { pipeline } from '@huggingface/transformers'; // Allocate pipeline const pipe = await pipeline('automatic-speech-recognition', 'huuquyet/PhoWhisper-medium');
File size: 1,358 Bytes
abda9df 8a991b2 abda9df 8a991b2 0f16d99 abda9df | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 | ---
license: wtfpl
language:
- vi
library_name: transformers.js
---
https://hf.co/vinai/PhoWhisper-medium with ONNX weights to be compatible with Transformers.js.
Please check out this demo using this model:
[](https://huggingface.co/spaces/huuquyet/PhoWhisper-next)
# PhoWhisper: Automatic Speech Recognition for Vietnamese
We introduce **PhoWhisper** in five versions for Vietnamese automatic speech recognition. PhoWhisper's robustness is achieved through fine-tuning the multilingual [Whisper](https://github.com/openai/whisper) on an 844-hour dataset that encompasses diverse Vietnamese accents. Our experimental study demonstrates state-of-the-art performances of PhoWhisper on benchmark Vietnamese ASR datasets. Please **cite** our PhoWhisper paper when it is used to help produce published results or is incorporated into other software:
```
@inproceedings{PhoWhisper,
title = {{PhoWhisper: Automatic Speech Recognition for Vietnamese}},
author = {Thanh-Thien Le and Linh The Nguyen and Dat Quoc Nguyen},
booktitle = {Proceedings of the ICLR 2024 Tiny Papers track},
year = {2024}
}
```
For further information or requests, please go to [PhoWhisper's homepage](https://github.com/VinAIResearch/PhoWhisper)! |